We estimate annual growth and mortality of red abalone, Haliotis rufescens, in northern California using tag recapture data applied to multiple growth and mortality models. We investigate seven growth models of the form, L _{t 1} = L_t f(L_t ) where L_t is the shell length at tagging (time t), L_{t 1}, is the shell length one year later, and the function f(L_t ) is a model of the change in length ΔL. Abalone are drawn from a broad range of sizes (shell lengths 5–222 mm) tagged and recaptured one year later (n = 231) in the Point Cabrillo Reserve in northern California. We present the results for seven growth models, rank the fit of the models (using the sum of the squared residuals) selecting the Richards, Gaussian, Ricker, and von Bertalanffy models (in that order) as most appropriate for these variable growth data. The von Bertalanffy model yields the shortest time to fishery (recreational legal size is 178 mm) as it slightly overestimates early growth. The Ricker model yields the longest time to enter the fishery underestimating early growth. We present a table of abalone sizes as a function of time for the Gaussian model, from which we estimate the number of years to grow into the fishery (12.0 ± 1 y). Because differences among the applicable models are not great, we use the growth parameters generated by the simple von Bertalanffy model (L_∞ and K) to estimate mortality. The results are consistent among our five mortality estimates ranging from 0.11–0.23 per year. Estimates of the number of years to enter the fishery and mortality estimates, as well as knowledge of how model selection can influence these estimates, is important for fishery management. Informed fishery management for red abalone is critical because the fishery in northern California is the last open abalone fishery in the state.